Assessment of Observer Based Fault Estimators for TS Fuzzy Models

Zahra Shams | Saeed Seyedtabaii

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URL :   http://research.shahed.ac.ir/WSR/WebPages/Report/PaperView.aspx?PaperID=43852
Date :  2017/03/07
Publish in :     5Th iranian joint conference on fuzzy and intelligent systems

Link :  http://ieeexplore.ieee.org/document/8003682/
Keywords :Observer, Estimators, Fuzzy

Abstract :

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Fault detection of nonlinear systems become more feasible when it is conducted over Takagi-Sugeno (TS) approximated fuzzy models. Proportional plus integral observer (PIO) and robust observer (RO) have already been developed for the estimation of the system states and actuator/sensor faults. The algorithms are implemented for the detection of valve and level sensor faults of a two-tank system. The simulation results indicate that both algorithms run well in estimating states and sensor fault, however, there is obvious differences in how they detect actuator fault in the presence of noise. From viewpoint of estimation variance, RO renders cleaner estimate of the fault than PIO, whiles PIO has faster fault tracking speed than RO. In general, the RO algorithm is recognized to be a more attractive in estimating actuator faults in noisy environments. The results are validated through simulations.

http://ieeexplore.ieee.org/document/8003682/